This is a Quarto document. Quarto combines text (like this) with code to create dynamic reports. These are examples of what you can do with Quarto: https://quarto.org/docs/gallery/. This tutorial will cover both R programming basics AND how to work with Quarto documents.
Quarto allows you to:
Load the required package and examine the data:
library(palmerpenguins)
Attaching package: 'palmerpenguins'The following objects are masked from 'package:datasets':
penguins, penguins_raw# Your code here: Explore the dataset structure
# How many rows? How many columns? What variable types?# Extract bill_length_mm as a vector
#bill_lengths <- # Your code here
# Calculate: mean, median, sd, min, max (handle NAs!)# Create logical vector: TRUE when bill length > 45mm
#long_bills <- # Your code here
# How many penguins have long bills?# Extract bill lengths for Dream island penguins only
# Calculate the mean for this subset# How many Adelie penguins are in the dataset?# Find: body mass, species, and island of the heaviest penguin# Remove rows with missing values
#penguins_complete <- penguins[complete.cases(penguins), ]
# Create matrix with: bill_length_mm, bill_depth_mm,
# flipper_length_mm, body_mass_g
#penguin_measurements <- # Your code here# Use apply() to calculate mean of each column
# Use apply() to find which row has the maximum for each column# Function that: removes NAs, returns (x - mean) / sd
#standardize <- function(x) {
# Your code here
#}
# Test on bill_length_mm
#bill_length_standardized <- standardize#(penguins$bill_length_mm)
# Verify: mean ≈ 0, sd ≈ 1Choose ONE bonus challenge:
Option A: Create a summary data frame with one row per species showing: count, mean body mass, mean flipper length
Option B: Calculate bill length-to-depth ratio for each penguin. Which species has the highest average ratio?
# Your bonus code here<-: Alt + - (minus)Remember: Save your work frequently (Ctrl/Cmd + S)!